PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Under Voltage Load Shedding Scheme Using Meta-heuristic Optimization Methods

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
PL
Meta-heurystyczne metody optymalizacyjne wykorzystywane do szybkiego pozbywania się obciążenia sieci
Języki publikacji
EN
Abstrakty
EN
Load shedding has been extensively studied because of multiple power system failure occurrences worldwide. Reliable techniques are required to provide rapid and precise load shedding to avert voltage collapse in power networks. Meta-heuristic optimization approaches are currently the widely developed methods because of their robustness and flexibility in dealing with complex and non-linear systems. These methods include genetic algorithm, fuzzy logic control, particle swarm optimization, artificial neural network, ant colony optimization, big-bang big-crunch optimization, and many others. This study provides an overview of all the meta-heuristic methods implemented for under voltage load shedding in power systems.
PL
Pozbywanie się obciążenia jest istotne z punktu widzenia możliwego zapadu systemu przesyłu energii. Do tego celu wykorzystuje się optymalizację meta-heurystyczną głównie dzięki odporności i szerokim możliwościom. W skład metody wchodzą: algorytm genetyczny, logika rozmyta, algorytmy mrówkowe, sieci neuronowe. W artykule dokonano przeglądu tych metod.
Rocznik
Strony
162--168
Opis fizyczny
Bibliogr. 46 poz., schem., tab.
Twórcy
autor
  • Dept. of Electrical, Electronics and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi, Malaysia
autor
  • Dept. of Electrical, Electronics and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi, Malaysia
autor
  • Dept. of Electrical, Electronics and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi, Malaysia
autor
  • Dept. of Electrical Power Engineering, Universiti Tenaga Nasional, Malaysia
Bibliografia
  • 1] Cutsem, T.V. Voltage instability: phenomena, countermeasures and analysis methods”, Proc. IEEE, 2000, 88, pp. 208–227
  • [2] Taylor, C.W., Erickson, E.C., Martin, K.E., Wilson, R.E. Ventakatasubramaniam, “WASC- wide area stability and voltage control system: R&D and online demonstration”, Proc. IEEE, 2005, 93, pp. 892- 906
  • [3] Sinha, A.K., Hazarika, D., “ A comparative study of voltage Stability indices in a power system”, Int. J. Electr. Power Energy System, 2000, 22, pp. 589–596
  • [4] Zarate, L.A.Ll., Castro, C.A.: ‘A critical evaluation of a maximum loading point estimation method for voltage stability analysis’, lectr. Power Syst. Res., 2004, 70, pp. 195–202
  • [5] Zambroni de Souza, A.C., Stacchini de Souza, J.C., Leite da Silva, A.M.: ‘On-line voltage stability monitoring’, IEEE Trans. Power Syst., 2000, 15, pp. 1300–1305
  • [6] Haque, M.H.: ‘On-line monitoring of maximum permissible loading of a power system within voltage stability limits’, IEEE Proc. ener. Transm. Distrib., 2000, 150, pp. 107–112
  • [7] Chebbo, A.M., Irving, M.R., Sterling, M.J.H.: ‘ Voltage collapse proximity indicator: behavior and implications’, IEE Proc. Gener. Transm. Distrib., 1992, 139, pp. 241–252
  • [8] Gao, B., Morison, G.K., Kundur, P.: ‘Voltage stability evaluation Using modal analysis’, IEEE Trans. Power Syst., 1992, 7, pp. 529–1542
  • [9] M. Dorigo, luca M. G., " Ant Colony system: A Cooperative learning approach to the Travelling Salesman Problem”,IEEE transaction on evolutionary computation, Vol. 1, No. 1, 1997.
  • [10] A. Colorni, M. Dorigo and V. Maniezzo, Distributed Optimization by ant colonies”, Proceedings of ECAL 91, European Conference on Artificial Life, Elsevier Publishing, Amsterdam,1991.
  • [11] David E Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning: Addison- Wesley, 1989.
  • [12] B. F. Rad and M. Abedi, "An optimal load-shedding scheme during contingency situations using meta-heuristics algorithms with application of AHP method," in 11th International Conference on Optimization of Electrical and Electronic Equipment, OPTIM 2008, pp. 167-173.
  • [13] W.P. Luan, M.R. Irving, J.S. Daniel, “Genetic Algorithm For Supply Restoration And Optimal Load Shedding In Power System Distribution Networks,” IEE Proceedings - Generation, Transmission and Distribution, Vol. 149, No. 2, March 2002, pp. 145 – 151.
  • [14] Wael M.AL-Hasawi, Khaled M.EL-Naggar, “ Optimum Steady State Load Shedding Scheme Using Genetic Based Algorithm”, 11th’ Mediterranean Electrotechnical Conference, (MELECONZOOZ), Cairo, Egypt,, May 2002, pp.605-609.
  • [15] K.A.Palaniswamy and J.Sharma “ Generation scheduling under emergency mode of operation”; All India Symposium on Power System Operation and Control”; Osmania University, Hyderabad, 1979, pp.2.3.1-2.3.
  • [16] M.A.Mostafa, M.E.El-Hawary, G.A.Mbamalu, M.M. Mansour, K.M.El-Nagar and A.N.El-Arabaty, “A Computational Comparison of Steady-state load shedding Approaches in Electrical Power Systems”, IEEE Trans. Power Systems, PW-12, (I), 1997, pp.30-37.
  • [17 ]Wang,Z.Zhongli,”The study on improved genetic algorithm'sap plication in under voltage load shedding”, International Conference Environmental Science and Information Technology 2010, Vol. 3, pp. 496- 498.
  • [18] Guichon, M. ; Dept. of Tech. Studies, Network Oper. Montevideo in UTE, Montevideo, Uruguay ; Melo, M. ; Nieto, A.C. ; Vignolo, M., “ Automatic Load Shedding calculated with Genetic Algorithms- DC- CMAG”, Transmission and Distribution: Latin America Conference and Exposition (T&DLA), 2012 Sixth IEEE/PES 2012 , Page(s): 1 – 7.
  • [19] J. Kennedy and R. Eberhart, “ Particle Swarm Optimization,” Proceedings of IEEE International Conference on Neural Networks, Vol. IV, pp. 1942-1948, Perth, Australia, 1995.
  • [20] Amraee, T. Mozafari, B., Ranjbar, A.M., “An improved model for optimal under voltage load shedding: particle swarm approach”, in IEEE Power India Conference, India, 2006.
  • [21] Sadati N, Amraee T, Ranjbar AM, “A global particle swarmbased-simulated annealing optimization technique for undervoltage load shedding problem”. Appl Soft Comput 2009;9:652–7.
  • [22] N. Sadati, M. Zamani, H. Mahdavian, “ Hybrid particle swarmbased-simulated annealing optimization techniques”, Proceedings of the IEEE Inter. Conf. onIndus. Elect. (IECON 2006), Paris, France, November 2006.
  • [23] B. A. Mozafari, T.;Ranjbar, A.M., "An Approach for Under Voltage Load Shedding using Particle Swarm Optimization," in IEEE International Symposium on Industrial Electronics. vol. 3 Montreal,Que, 2006, p. 1.
  • [24] M. Tarafdar Hagh, S. Galvani, “Minimization of load shedding by sequential use of linear programming and particle swarm optimization”, Turkish Journal of Electrical Engineering & Computer Sciences, Vol. 19, pp. 551-563, 2011.
  • [25] Jalilzadeh, S., Hosseini, S.H., Derafshian-Maram, M., “Optimal load shedding to prevent voltage instability based on multiobjective optimization using modal analysis and PSO”, in International Congress on Ultra-Modern Telecommunications and Control Systems and Workshops (ICUMT), Moscow, 2010, pp. 371 – 376.
  • [26] K.-H. Han, J.-H. Kim, "Quantum-inspired evolutionary algorithm for a class of combinatorial optimization," IEEE Transactions on Evolutionary Computation, vol. 6, no. 6, Dec. 2002, pp. 580-593.
  • [27] Yasin, Z.M., Rahman, T.K.A., Zakaria, Z, “Optimal undervoltage load shedding using Quantum-Inspired Evolutionary Programming”, IEEE TENCON Spring Conference, Sydney, 2013, pp. 337 – 341.
  • [28] Yasin, Z.M., Rahman, T.K.A., Zakaria, Z, “Quantum-Inspired Evolutionary Programming-Artificial Neural Network for prediction of undervoltage load shedding”, 8th IEEE Conference on Industrial Electronics and Applications (ICIEA), Melbourne, June 2013, pp. 583 – 588.
  • [29] M. Dorigo and G. Di Caro. The Ant Colony Optimization metaheuristic. New Ideas in Optimization, pages 11–32: McGraw Hill, London, UK, 1999).
  • [30] M. Dorigo, L. M. Gambardella, M. Middendorf, T. Stützle, “ Ant Algorithms and Swarm Intelligence”, Special issue on IEEE Transactions on Evolutionary Computation, 2002.
  • [31] W. Nakawiro and I. Erlich, "Optimal Load Shedding for Voltage Stability Enhancement by Ant Colony Optimization," 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09., 2009, pp. 1-6.
  • [32] Erol OK, Eksin I, “A new optimization method: Big Bang-Big Crunch.”, Adv Eng Softw 2006; vol 37:106–11.
  • [33] S. Sakthivel , D. Mary. “Big Bang-Big Crunch Algorithm for Voltage Stability Limit Improvement by Coordinated Control of SVC Settings”, Research Journal of Applied Sciences, Engineering and Technology, vol 6(7): 1209-1217, 2013.
  • [34] Das S, Biswas A, Dasgupta S, Abraham. Bacterial foraging optimization algorithm: theoretical foundations, analysis, and applications, foundations of computational intelligence. Global optimization, studies in computational intelligence, vol 3. Springer, Germany, pp 23–55. 2009
  • [35] Afandie, W.N.E.A.W, Rahman, T.K.A, Zakaria, Z, “Bacterial foraging optimization algorithm for load shedding”, IEEE 7th International Power Engineering and Optimization Conference (PEOCO), 2013, Langkawi, pp. 722 – 726.
  • [36] Haidar AMA, Mohamed A, Hussain A. “Vulnerability control of large scale interconnected power system using neuro-fuzzy load leadding approach”, Exp Syst Appl 2010;37:3171–6.
  • [37] Sasikala J, Ramaswamy M., “Fuzzy based load shedding strategies for avoiding voltage collapse”, Appl Soft Comput 2011; vol 11:3179–85.
  • [38] Sallam AA, Khafaga AM. Fuzzy expert system using load shedding for voltage instability control. Eng Syst Conf Power Eng 2002:125–32.
  • [39] Zulkiffli Abdul Hamid, Ismail Musirin, “Optimal Fuzzy Inference System incorporated with stability index tracing: An application for effective load shedding”, Expert Syst. Appl. 41(4): 1095-1103 (2014).
  • [40] Tso SK, Zhu TX, Zeng QY, Lo KL, “ Evaluation of load shedding to prevent dynamic voltage instability based on extended fuzzy reasoning”, IET GenerationTransmission, Dis 1997;144:81–6.
  • [41] T. Van Cutsem, C. Moors, and D. Lefebvre, “Design of load shedding schemes against voltage instability using combinatorial optimization,” in Proc. IEEE Power Eng. Soc. Winter Meeting, New York, 2002.
  • [42] D. Lefebvre, C. Moors, and T. V. Custem, “Design of an undervoltage load shedding scheme for the Hydro-Quebec system,” in Proc. IEEE PES General Meeting, 2003.
  • [43] Xin-She Yang, “Firefly Algorithm: Recent Advances and Applications”, arXiv:1308.3898v1, 18 Aug 2013.
  • [44] Civicioglu, P., “Backtracking Search Optimization Algorithm fornumerical optimization problems”, Applied Mathematics and Computation, Vol 219, Issue 15, 2013, pp. 8121-8144.
  • [45] R. Verayiah, A. Mohamed, H.Shareef, I. Z. Abidin, “Review of Under-voltage Load Shedding Schemes in Power System Operation” PRZEGLĄD ELEKTROTECHNICZNY, 2014, 90, pp.99 -103.
  • [46] J.A. Laghari, H. Mokhlis, A.H.A. Bakar, H. Mohamad., “Application of computational intelligence techniques for load shedding in power systems: A review”, Energy Conversion and Management, 2013, 75, pp. 130-140.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7160cc70-ab4f-4bde-8d11-406b9bcf6b04
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.